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Dataset specification · Domain scale

250 hours of Marathi Conversational Speech

A domain scale build of 250 hours of Marathi conversational speech. Fine-tuning a production model for a specific domain, accent range or deployment condition. Two speakers hold an unscripted conversation seeded with a scenario, recorded on separate channels so overlap and turn-taking survive into the delivered files.

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Two speakers recording natural conversational speech data — 250 hours of Marathi Conversational Speech
Volume
250 hours
Scale
Domain scale
Per speaker
20–30 minutes of accepted audio per speaker, in pairs
Accepted yield
55–65% of recorded time is accepted
01

How Marathi conversational speech is captured

Two speakers hold an unscripted conversation seeded with a scenario, recorded on separate channels so overlap and turn-taking survive into the delivered files.

A 45–60 minute paired session with both speakers on isolated microphones, either in adjacent treated rooms or split-mic in one room with bleed measured and logged.

Yield at this style: 55–65% of recorded time is accepted. Overlap regions, crosstalk bleed and one-sided stretches all cost delivered time. The lowest-yield studio style we run, and priced accordingly.

Domain scale — what the build is actually made ofCitiesThree to fourStudiosThree to four rooms plu…RecruitersFour coordinators under…Speakers~500–600Sessions per day25–30 nationallyTeam1 programme lead, 4 coo…
02

The specification

FieldValue
LanguageMarathi (mr-IN, Devanagari)
Volume250 hours
Equivalent500 speakers at 30 minutes each, or 250 speakers at one hour each
Speech typeConversational Speech
Per speaker20–30 minutes of accepted audio per speaker, in pairs
ChannelsTwo, one per speaker, never mixed down before delivery
Channel isolationBleed measured per session and logged; sessions over threshold are re-recorded
OverlapPreserved, timestamped and labelled rather than edited out
File granularityPer-channel session WAV plus a turn-level manifest with speaker IDs
DialectsStandard (Puneri), Varhadi (Vidarbha), Marathwadi, Konkani-influenced coastal Marathi
TranscriptionVerbatim, native-speaker, second-pass reviewed
Transcriber timestamping Indian language audio — supporting 250 hours of marathi conversational speech
Transcriber timestamping Indian language audio
03

Designing the scenarios for Marathi

  • Scenario seeds rather than scripts — a disagreement to resolve, a plan to make, an experience to compare
  • Pairing designed deliberately: familiar pairs produce natural interruption, stranger pairs produce polite turn-taking, and you need both
  • Scenarios that invite disagreement, because agreeable conversation produces almost no overlap to train on
  • Register mixed across pairs so the corpus is not uniformly formal
  • Built against Marathi specifically: Retains the retroflex lateral ळ, which has no Hindi or English equivalent and is frequently substituted with ल by non-native transcribers
  • Code-mixing handled explicitly rather than edited out — Mumbai and Pune speech mixes Marathi, Hindi, and English in the same sentence. Marathi-only recordings collected in Pune under-represent the Mumbai reality of tri-lingual switching.
04

Running a domain scale Marathi build

Six to eight weeks. Beyond three cities the bottleneck moves from recruitment to transcription throughput, which is why the transcriber count rises faster than the engineer count.

Four to five batches on a fortnightly cadence, sequenced so the dialects you care about most land first.

A representative Marathi cohort should be split roughly 40% western Maharashtra, 25% Vidarbha, 20% Marathwada, 15% Konkan rather than concentrated in Pune.

ParameterAt this volume
CitiesThree to four — Mumbai, Pune, Nagpur, Nashik
StudiosThree to four rooms plus one mobile rig
RecruitersFour coordinators under one programme lead
Speakers~500–600
Sessions per day25–30 nationally
Team1 programme lead, 4 coordinators, 8 engineers, 14 transcribers, 2 QA leads
05

Cohort design

At 250 hours quotas are enforced per dialect and reconciled fortnightly. Aggregate demographics are reported per batch so drift is visible while there is still time to correct it.

Effectively doubles recruitment load, since speakers are booked in matched pairs and a single drop-out cancels the whole session. Plan on 20–25% over-recruitment.

DimensionTypical splitWhy it matters for Marathi
Gender50 / 50Pitch range differences change acoustic model behaviour; unbalanced cohorts bias recognition
Age18-25: 30%, 26-40: 40%, 41-60: 30%Older speakers retain conservative Marathi forms that younger urban speakers have lost
RegionMaharashtra / Goa / parts of Karnataka and othersDialect spread across 6 recognised varieties
EducationMixed, including below-graduatePrompt-reading fluency correlates with education and skews prosody
ConditionStudio / quiet room / fieldMatch the noise profile of your deployment
06

Marathi-specific considerations

  • Retains the retroflex lateral ळ, which has no Hindi or English equivalent and is frequently substituted with ल by non-native transcribers
  • Mumbai and Pune speech mixes Marathi, Hindi, and English in the same sentence. Marathi-only recordings collected in Pune under-represent the Mumbai reality of tri-lingual switching.
  • Available Marathi speech data is dominated by standard Puneri read speech. Vidarbha, Marathwada, and coastal Konkan varieties are severely under-collected, which is exactly where deployed voice products lose accuracy.
07

Quality gates for conversational speech

  • Channel bleed measured on every session and rejected above the agreed threshold
  • Diarisation labels verified against the isolated channels rather than inferred from the mix
  • Turn boundaries and overlap regions checked by a native listener
  • Speaking-time balance per pair audited, so a dominant speaker does not silently halve the session's value
  • ळ vs ल substitution by Hindi-trained transcribers
  • Anusvara placement varies between conservative and modern orthography

100% technical QA, 15% content QA with stratified sampling across city, dialect and transcriber, so no single team's output goes unchecked.

08

What goes wrong on conversational speech sessions

  • Crosstalk bleed that makes clean per-speaker training targets impossible to recover afterwards
  • One speaker dominating, leaving a pair that delivers half the expected audio
  • Unnatural politeness between strangers, producing clean but unrepresentative turn-taking
  • Scheduling attrition — both speakers have to show up, so no-show rates compound rather than add
09

Risks at domain scale in Marathi

Cost at this band is driven by: Transcription depth — verbatim with disfluencies costs materially more than clean-read transcription; Number of distinct dialect quotas rather than raw hours.

  • Transcription becomes the critical path and stays there for the rest of the volume bands
  • Coordinator turnover mid-build causes quota drift that is only visible in the final demographic report unless it is audited weekly
  • Marathi carries 6 recognised varieties across Maharashtra, Goa, parts of Karnataka, so the quota matrix is wider than the headline volume suggests
  • Available Marathi speech data is dominated by standard Puneri read speech. Vidarbha, Marathwada, and coastal Konkan varieties are severely under-collected, which is exactly where deployed voice products lose accuracy.
10

Deliverables

  • WAV audio to your naming convention, with the per-file manifest
  • Verbatim Devanagari transcripts with utterance-level timestamps
  • Speaker-turn segmentation with start and end timestamps
  • Overlap regions marked with participating speaker IDs
  • Backchannel and interruption markers
  • Per-pair relationship metadata: familiar or stranger
  • Per-speaker metadata: age band, gender, region, dialect, education band
  • Consent records mapped to speaker IDs
  • QA report with pass rates, rejection reasons and agreement statistics
  • Speaker-disjoint train / dev / test splits on request
11

What this trains, and what it does not

  • Speaker diarisation
  • Meeting and multi-party ASR
  • Turn-taking and endpointing for voice agents
  • Speaker separation and target-speaker extraction

Two-party conversation does not generalise to multi-party meetings with four or more speakers, where overlap statistics change substantially. Specify that case separately.

Frequently asked

Is 250 hours of Marathi enough?

Enough to shift word error rate meaningfully on a domain-specific deployment. For a general-purpose model in a low-resource language, still a starting layer.

Why conversational speech rather than another speech type?

Speaker diarisation, Meeting and multi-party ASR, Turn-taking and endpointing for voice agents are what this style is the right input for. Two-party conversation does not generalise to multi-party meetings with four or more speakers, where overlap statistics change substantially. Specify that case separately.

How long does a domain scale Marathi build take?

Six to eight weeks. Beyond three cities the bottleneck moves from recruitment to transcription throughput, which is why the transcriber count rises faster than the engineer count. Four to five batches on a fortnightly cadence, sequenced so the dialects you care about most land first.

What does 250 hours of Marathi conversational speech cost?

Quoted per delivered hour against this specification. At this band the drivers are transcription depth — verbatim with disfluencies costs materially more than clean-read transcription and number of distinct dialect quotas rather than raw hours. Send the spec and you get one fixed figure.

How much QA is applied at this volume?

100% technical QA, 15% content QA with stratified sampling across city, dialect and transcriber, so no single team's output goes unchecked.

Quote this Marathi dataset

250 hours, conversational speech, Marathi — domain scale. Adjust anything and send it.

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